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Rosstat data on the dynamics of major socially significant diseases have been studied. The relationship between such diseases has been investigated. The influence of the main socially significant diseases and the main indicators of socio-economic development of the regions of the Russian Federation on the number of abortions has been studied. The most informative signs related to socially significant diseases and socio-economic development in all countries of the world have been selected. The influence of these signs on infant mortality has been studied. Machine learning methods collected in the Data Master Azforus (DMA) program were applied. The conducted research has demonstrated the effectiveness of using machine learning methods to identify patterns linking the frequency of socially significant diseases and indicators of socio-economic development.

Cilia are cell surface organelles with key roles in a range of cellular processes, including generation of fluid flow by motile cilia. The axonemes of motile cilia and immotile kinocilia contain 9 peripheral microtubule doublets, a central microtubule pair, and 9 connecting radial spokes. Aberrant radial spoke components RSPH1, 3, 4a and 9 have been linked with primary ciliary dyskinesia (PCD), a disorder characterized by ciliary dysmotility; yet, radial spoke functions remain unclear. Here we show that zebrafish Rsph9 is expressed in cells bearing motile cilia and kinocilia, and localizes to both 9 + 2 and 9 + 0 ciliary axonemes. Using CRISPR mutagenesis, we show that rsph9 is required for motility of presumptive 9 + 2 olfactory cilia and, unexpectedly, 9 + 0 neural cilia. rsph9 is also required for the structural integrity of 9 + 2 and 9 + 0 ciliary axonemes. rsph9 mutant larvae exhibit reduced initiation of the acoustic startle response consistent with hearing impairment, suggesting a novel role for Rsph9 in the kinocilia of the inner ear and/or lateral line neuromasts. These data identify novel roles for Rsph9 in 9 + 0 motile cilia and in sensory kinocilia, and establish a useful zebrafish PCD model.

The paper considers cold rolling simulation during the continuous annealing process. The development of a simulation model of the considered process is relevant as it makes it possible to predict the mechanical properties of steel, such as yield stress, ultimate resistance, tensile strain, without a natural experiment. Dynamic neighborhood models are applied for the simulation of complex distributed production processes and systems. They reflect the dynamics of the considered process and make it possible to control its results at the intermediate production stages. A general definition of dynamic neighborhood models with a fuzzy hierarchical structure is given, the models being characterized by fuzzy neighborhood two-level links between the model nodes of the first and second level. In the paper, linear fuzzy hierarchical dynamic neighborhood models of the cold rolling process for calculating the mechanical properties of steel are developed. The simulated and production data on the basis of relative identification errors are analyzed and conclusions are made. [ABSTRACT FROM AUTHOR]

The paper considers and simulates a neural network-based strip cooling process in a hot-strip mill. This process is outlined in a figure highlighting the main functional areas. A hybrid algorithm for training a radial basis neural network is described. A program was developed in the Mathcad programming unit to implement the mathematical model of the researched neural network. The input and output variables of the strip cooling process were selected, the initial data were normalized. Training and validation samples are drawn using Microsoft Access queries. A number of computational experiments were conducted for this model to obtain the optimum structure and parameters of the radial basis neural network. The results of neural network training, graphs of deviations of model values from the set ones in training and validation samples are given. The root-mean-square and relative network errors were found using the unnormalized output data. [ABSTRACT FROM AUTHOR]